SoroushVahidi/scidocs huggingface dataset:
Differentiating optic disc edema from optic nerve head drusen on optical coherence tomography.
(2009)

OBJECTIVE
To assess optical coherence tomography in differentiating optic disc edema (ODE) due to papilledema and other optic neuropathies from optic nerve head drusen (ONHD).


METHODS
Optical coherence tomographic images from 60 subjects (20 with ODE, 20 with ONHD, and 20 control subjects) were assessed qualitatively and quantitatively. Qualitative criteria for ODE included an elevated optic nerve head with smooth internal contour and subretinal hyporeflective space (SHYPS) with recumbent "lazy V" pattern. Optic nerve head drusen displayed a "lumpy-bumpy" internal optic nerve contour and a rapid decline in SHYPS thickness. Quantitative comparisons included retinal nerve fiber layer and SHYPS thickness.


RESULTS
Optical coherence tomography differentiated ODE from ONHD qualitatively (sensitivity, 63%; specificity, 63%) and quantitatively (sensitivity, 80%; specificity, 90%). Respective differences in mean retinal nerve fiber layer thickness between ODE and ONHD were significant (P < .002) superiorly (206.8 vs 121.7 microm), nasally (176.3 vs 78.6 microm), inferiorly (247.2 vs 153.8 microm), and temporally (180.0 vs 85.5 microm). Respective differences in mean SHYPS thickness between ODE and ONHD were significant (P < .001) at radii of 0.75 mm (512.1 vs 274.4 microm), 1.5 mm (291.4 vs 103.0 microm), and 2.0 mm (145.5 vs 60.7 microm).


CONCLUSION
Optical coherence tomography can differentiate ODE from ONHD, particularly when the nasal retinal nerve fiber layer and SHYPS thickness at the 2.0-mm radius are greater than 86 microm and 127 microm, respectively.
Trajectory planning and tracking of ball and plate system using hierarchical fuzzy control scheme
(2004)

Ball and plate system is the extension of traditional ball and beam system. In this paper, a trajectory planning and tracking problem of ball and plate system is put forward to proof-test diverse control schemes. Firstly, we derive the mathematical model of the ball and plate system in detail. Then a hierarchical fuzzy control scheme is proposed to deal with this problem. Our scheme is composed of three levels. The lowest level is a TS type fuzzy tacking controller; the middle level is a fuzzy supervision controller that takes actions in extreme situations; and the top level is a fuzzy planning controller that determines the desired trajectory. In order to optimize the ball’s moving trajectory, the genetic algorithm is introduced to adjust the output membership functions of the fuzzy planning controller. Simulation results have shown that the hierarchical fuzzy control scheme can control the ball from a point to another without hitting the obstacles and in the least time. c © 2003 Elsevier B.V. All rights reserved.
Anomaly detection and monitoring in Internet of Things communication
(2016)

The Internet of Things (IoT) presents unique challenges in detecting anomaly and monitoring all connected devices in a network. Moreover, one of the objectives of anonymity in communication is to protect the data traffic of devices. The summary status visualization is indispensable to depict all devices/sensors that are most indicative of a pending failure and a predictive power/energy. Thus, this paper proposes a multi-platform monitoring and anomaly detection system that supports heterogeneous devices. The proposed system addresses the problems of: (i) how to monitor the network to prevent device failures and (ii) how to design a comprehensive feature for the early anomaly detection of IoT communication.
Fractional Order ControlA Tutorial
(2009)

Many real dynamic systems are better characterized using a non-integer order dynamic model based on fractional calculus or, differentiation or integration of noninteger order. Traditional calculus is based on integer order differentiation and integration. The concept of fractional calculus has tremendous potential to change the way we see, model, and control the nature around us. Denying fractional derivatives is like saying that zero, fractional, or irrational numbers do not exist. In this paper, we offer a tutorial on fractional calculus in controls. Basic definitions of fractional calculus, fractional order dynamic systems and controls are presented first. Then, fractional order PID controllers are introduced which may make fractional order controllers ubiquitous in industry. Additionally, several typical known fractional order controllers are introduced and commented. Numerical methods for simulating fractional order systems are given in detail so that a beginner can get started quickly. Discretization techniques for fractional order operators are introduced in some details too. Both digital and analog realization methods of fractional order operators are introduced. Finally, remarks on future research efforts in fractional order control are given.
Machine Learning Approaches for Catchphrase Extraction in Legal Documents
(2017)

The purpose of this research was to automatically extract catchphrases given a set of Legal documents. For this task, our focus was mainly on the Machine learning approaches: a comparative approach was used between the unsupervised and supervised approaches. The idea was to compare the different approaches to see which one of the two was comparatively better for automatic catchphrase extraction given a dataset of Legal documents. To perform this, two open source text mining software were used; one for the unsupervised approach while another one was used for the supervised approach. We then fine tuned some parameters for each tool before extracting catchphrases. The training dataset was used when fine tuning parameters in order to find optimal parameters that were then used for generating the final catchphrases. Different metrics were used to evaluate the results. We used the most common measures in Information Extraction which include Precision and Recall and the results from the two Machine learning approaches were compared. In general our results showed that the supervised approach performed far much better than the unsupervised approach.
Truthful incentives in crowdsourcing tasks using regret minimization mechanisms
(2013)

What price should be offered to a worker for a task in an online labor market? How can one enable workers to express the amount they desire to receive for the task completion? Designing optimal pricing policies and determining the right monetary incentives is central to maximizing requester's utility and workers' profits. Yet, current crowdsourcing platforms only offer a limited capability to the requester in designing the pricing policies and often rules of thumb are used to price tasks. This limitation could result in inefficient use of the requester's budget or workers becoming disinterested in the task.
 In this paper, we address these questions and present mechanisms using the approach of regret minimization in online learning. We exploit a link between procurement auctions and multi-armed bandits to design mechanisms that are budget feasible, achieve near-optimal utility for the requester, are incentive compatible (truthful) for workers and make minimal assumptions about the distribution of workers' true costs. Our main contribution is a novel, no-regret posted price mechanism, BP-UCB, for budgeted procurement in stochastic online settings. We prove strong theoretical guarantees about our mechanism, and extensively evaluate it in simulations as well as on real data from the Mechanical Turk platform. Compared to the state of the art, our approach leads to a 180% increase in utility.
A hierarchical framework for evaluating simulation software
(1999)

In simulation software selection problems, packages are evaluated either on their own merits or in comparison with other packages. In either method, a comprehensive list of criteria for evaluation of simulation software is essential for proper selection. Although various simulation software evaluation checklists do exist, there are dierences in the lists provided and the terminologies used. This paper presents a hierarchical framework for simulation software evaluation consisting of seven main groups and several subgroups. An explanation for each criterion is provided and an analysis of the usability of the proposed framework is further discussed. Ó 1999 Elsevier Science B.V. All rights reserved.
Applying Deep Learning to Enhance Momentum Trading Strategies in Stocks
(2013)

We use an autoencoder composed of stacked restricted Boltzmann machines to extract features from the history of individual stock prices. Our model is able to discover an enhanced version of the momentum effect in stocks without extensive hand-engineering of input features and deliver an annualized return of 45.93% over the 1990-2009 test period versus 10.53% for basic momentum.
A New Method for Optimization of Dynamic Ride Sharing System
(2015)

Dynamic ridesharing is a profitable way to reduce traffic and carbon emissions by providing an opportunity for a flexible and affordable service that utilizes vehicle seating space. Matching of ride seeker requests with the rides, distributed over the roads is a tedious work. While fulfilling the request of all passengers, the total travel distance of the trip may get increased. Therefore, this article proposes optimal dynamic ridesharing system which matches rides and requests in real time by satisfying multiple participant constraints (e.g. time bounds, availability of empty seat, maximum allowed deviation distance and minimized route ride) to minimize the total travel distance. To efficiently match ride givers and riders we are proposing a novel dynamic ride matching algorithm MRB (Minimal route bisearching algorithm) considering all above mentioned constraints. We demonstrate working of our algorithm by developing a prototype and evaluated our system on GPS (Global positioning system) trajectories of Lahore city dataset. Evaluated results are compared with existing algorithms which shows that our system significantly reduces the travel distance and computation cost in comparison with other recent ride searching methods to maximize efficiency.
On the Effectiveness of Ambient Sensing for Detecting NFC Relay Attacks
(2017)

Smartphones with Near-Field Communication (NFC) may emulate contactless smart cards, which has resulted in the deployment of various access control, transportation and payment services, such as Google Pay and Apple Pay. Like contactless cards, however, NFC-based smartphone transactions are susceptible to relay attacks, and ambient sensing has been suggested as a potential countermeasure. In this study, we empirically evaluate the suitability of ambient sensors as a proximity detection mechanism for smartphone-based transactions under EMV constraints. We underpin our study using sensing data collected from 17 sensors from an emulated relay attack test-bed to assess whether they can thwart such attacks effectively. Each sensor, where feasible, was used to record 350-400 legitimate and relay (illegitimate) contactless transactions at two different physical locations. Our analysis provides an empirical foundation upon which to determine the efficacy of ambient sensing for providing a strong anti-relay mechanism in security-sensitive applications. We demonstrate that no single, evaluated mobile ambient sensor is suitable for such critical applications under realistic deployment constraints.
Compact 4-element MIMO antenna with isolation enhancement for 4G LTE terminals
(2016)

In this work, a wide-band, planar, printed inverted-F antenna (PIFA) is proposed with multiple-input-multiple-output (MIMO) antenna configuration. The MIMO antenna system consists of 4-elements operating at 2.1 GHz frequency band for 4G LTE applications. The proposed design is compact, low profile and suitable for wireless handheld devices. The MIMO antenna is fabricated on commercially available FR4 substrate with εr equal to 4.4. The dimensions of single element are 26×6 mm2 with board volume equal to 100×60×0.8 mm3. Isolation is improved by 5 dB in the proposed design using ground slots. Characteristics mode analysis (CMA) is used to analyze the behaviour of the antenna system.
LIMERIC: a linear message rate control algorithm for vehicular DSRC systems
(2011)

Wireless vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication holds great promise for significantly reducing the human and financial costs of vehicle collisions. A common characteristic of this communication is the broadcast of a device's core state information at regular intervals (e.g. a vehicle's speed and location, or a traffic signal's state and timing). The aggregate of these uncoordinated broadcasts will lead to channel congestion under dense traffic scenarios, with a resulting reduction in the effectiveness of the collision avoidance applications making use of the transmitted information. Active congestion control using distributed techniques is a topic of great interest for establishing the scalability of this technology for deployment. This paper defines a new congestion control algorithm that can be applied to the message rate of devices in this vehicular environment. While other published approaches rely on binary control, the LInear MEssage Rate Integrated Control (LIMERIC) algorithm takes advantage of full precision control inputs that are available on the wireless channel. The result is provable convergence to fair and efficient channel utilization in the deterministic environment, under simple criteria for setting adaptive parameters. This "perfect" convergence avoids the limit cycle behavior inherent to binary control. We also discuss several practical aspects associated with implementing LIMERIC, including: guidelines for the choice of system parameters to obtain desired utilization outcomes, a gain saturation technique that maintains robust stability under all conditions, convergence with asynchronous updates, and the implications of measurement noise for statistical properties of convergence. The paper illustrates key analytical results using MATLAB numerical results, and employs standard NS-2 simulations to demonstrate the performance of LIMERIC in several high density scenarios.
Measuring cultural awareness in nursing students.
(2003)

Recognizing the need for a valid and reliable way to measure outcomes of a program to promote multicultural awareness among nursing faculty and students, the authors developed a cultural awareness scale. In the first phase of the study, a scale consisting of 37 items was generated from a literature review on cultural awareness, sensitivity, and competence in nursing. A Cronbach's alpha reliability coefficient of .91 was obtained from a sample of 72 student nurses. In the second phase, the items were presented to a panel of experts in nursing and culture to determine content validity. A content validity index of .88 was calculated, and the total number of items on the scale was reduced to 36. The scale then was administered to 118 nursing students. Data from the two samples then were combined, and factor analysis was conducted to support construct validity. Cronbach's alpha for the combined samples was .82.
CORPORATE SOCIAL RESPONSIBILITY IN EMERGING MARKETS
(2018)

Purpose: This paper analyses CSR initiatives in emerging markets from developed-countriesbased multinational companies (MNCs). Methods: The analysis is based on eight case studies with data collected through in-depth interviews with senior managers of the companies representing 85% of the Spanish foreign investments in Latin America. Results: The results show that CSR initiatives from these companies seem to be guided by Instrumental Theories as they use these initiatives as a strategic tool to achieve economic objectives, seek a positive relation between them and their financial performance, and use them to strengthen their reputation. Conclusions: The findings tend to indicate that Instrumental Theories of CSR seem to apply for Western MNCs operating in emerging markets.
Dynamics of projective adaptive resonance theory model: the foundation of PART algorithm
(2004)

Projective adaptive resonance theory (PART) neural network developed by Cao and Wu recently has been shown to be very effective in clustering data sets in high dimensional spaces. The PART algorithm is based on the assumptions that the model equations of PART (a large scale and singularly perturbed system of differential equations coupled with a reset mechanism) have quite regular computational performance. This paper provides a rigorous proof of these regular dynamics of the PART model when the signal functions are special step functions, and provides additional simulation results to illustrate the computational performance of PART.
OpenHSM: An Open Key Life Cycle Protocol for Public Key Infrastructure's Hardware Security Modules
(2007)

The private keys used in a PKI are its most important asset. Protect these keys from unauthorised use or disclosure is essential to secure a PKI. Relying parties need assurances that the private key used to sign their certificates is controlled and managed following pre-defined statement policy. Hardware Security Modules (HSM) offer physical and logical protection and should be considered for any PKI deployment. The software that manages keys inside an HSM should control all life cycle of a private key. Normally this kind of equipment implements a embedded key management protocol and this protocols are not available to public scrutiny due to industrial interests. Other important issue is that HSMs are targeted in their development to the Bank industry and not to PKI, making some important PKI issues, like, strict key usage control and a secure auditing trail, play a secondary role. This paper presents an open protocol to securely manage private keys inside HSMs. The protocol is described, analysed and discussed.
Knowledge Begets Knowledge: Steps towards Assisted Knowledge Acquisition in Cyc
(2005)

The Cyc project is predicated on the idea that, in order to be effective and flexible, computer software must have an understanding of the context in which its tasks are performed. We believe this context is what is known informally as “common sense.” Over the last twenty years, sufficient common sense knowledge has been entered into Cyc to allow it to more effectively and flexibly support an important task: increasing its own store of world knowledge. In this paper, we describe the Cyc knowledge base and inference system, enumerate the means that it provides for knowledge elicitation, including some means suitable for use by untrained or lightly trained volunteers, review some ways in which we expect to have Cyc assist in verifying and validating collected knowledge, and describe how we expect the knowledge acquisition process to accelerate in the future.
Spinal and supraspinal factors in human muscle fatigue.
(2001)

Muscle fatigue is an exercise-induced reduction in maximal voluntary muscle force. It may arise not only because of peripheral changes at the level of the muscle, but also because the central nervous system fails to drive the motoneurons adequately. Evidence for "central" fatigue and the neural mechanisms underlying it are reviewed, together with its terminology and the methods used to reveal it. Much data suggest that voluntary activation of human motoneurons and muscle fibers is suboptimal and thus maximal voluntary force is commonly less than true maximal force. Hence, maximal voluntary strength can often be below true maximal muscle force. The technique of twitch interpolation has helped to reveal the changes in drive to motoneurons during fatigue. Voluntary activation usually diminishes during maximal voluntary isometric tasks, that is central fatigue develops, and motor unit firing rates decline. Transcranial magnetic stimulation over the motor cortex during fatiguing exercise has revealed focal changes in cortical excitability and inhibitability based on electromyographic (EMG) recordings, and a decline in supraspinal "drive" based on force recordings. Some of the changes in motor cortical behavior can be dissociated from the development of this "supraspinal" fatigue. Central changes also occur at a spinal level due to the altered input from muscle spindle, tendon organ, and group III and IV muscle afferents innervating the fatiguing muscle. Some intrinsic adaptive properties of the motoneurons help to minimize fatigue. A number of other central changes occur during fatigue and affect, for example, proprioception, tremor, and postural control. Human muscle fatigue does not simply reside in the muscle.
A Multiple Instance Learning Framework for Identifying Key Sentences and Detecting Events
(2016)

State-of-the-art event encoding approaches rely on sentence or phrase level labeling, which are both time consuming and infeasible to extend to large scale text corpora and emerging domains. Using a multiple instance learning approach, we take advantage of the fact that while labels at the sentence level are difficult to obtain, they are relatively easy to gather at the document level. This enables us to view the problems of event detection and extraction in a unified manner. Using distributed representations of text, we develop a multiple instance formulation that simultaneously classifies news articles and extracts sentences indicative of events without any engineered features. We evaluate our model in its ability to detect news articles about civil unrest events (from Spanish text) across ten Latin American countries and identify the key sentences pertaining to these events. Our model, trained without annotated sentence labels, yields performance that is competitive with selected state-of-the-art models for event detection and sentence identification. Additionally, qualitative experimental results show that the extracted event-related sentences are informative and enhance various downstream applications such as article summarization, visualization, and event encoding.
LTE for vehicular networking: a survey
(2013)

A wide variety of applications for road safety and traffic efficiency are intended to answer the urgent call for smarter, greener, and safer mobility. Although IEEE 802.11p is considered the de facto standard for on-the-road communications, stakeholders have recently started to investigate the usability of LTE to support vehicular applications. In this article, related work and running standardization activities are scanned and critically discussed; strengths and weaknesses of LTE as an enabling technology for vehicular communications are analyzed; and open issues and critical design choices are highlighted to serve as guidelines for future research in this hot topic.
3GPP LTE Versus IEEE 802.11p/WAVE: Which Technology is Able to Support Cooperative Vehicular Safety Applications?
(2012)

The concept of vehicular ad-hoc networks enables the design of emergent automotive safety applications, which are based on the awareness among vehicles. Recently, a suite of 802.11p/WAVE protocols aimed at supporting car-to-car communications was approved by IEEE. Existing cellular infrastructure and, above all 3GPP LTE, is being considered as another communication technology appropriate for vehicular applications. This letter provides a theoretical framework which compares the basic patterns of both the technologies in the context of safety-of-life vehicular scenarios. We present mathematical models for the evaluation of the considered protocols in terms of successful beacon delivery probability.